Selko modules:

The elicitation module allows the user to import documents and automatically extract requirement data into a list format.

The requirements can then be analyzed using other REA modules, or exported in global formats that integrate easily with most software tools.

The core technology of the elicitation module is the extraction pipeline, which reads the raw data from the documents source, then cleans the data, removing irrelevant information, and finally determines which parts of the remaining data constitute valid requirements.

Both the cleaning phase and the final detection phase utilize advanced statistical and semantical analysis techniques that mean to capture the knowledge that is represented in the imported texts.

This module aims to establish the quality status of imported requirements.

The module analyzes each requirement separately and delivers individual aspects of the overall quality of the requirement.

For instance, the module determines whether a given requirement is poorly written, if it contains enough data to represent an independent piece of information, if the statement of the requirement’s content is specific enough.

Techniques from Computational Linguistics are used here to perform the analysis. Examples include grammar and syntax models, domain-specific ontologies, language models build for the current field.

This module concentrates on how two or more requirements connect or relate to each other.

The module detects different types of relationships between the requirements, such as how similar two requirements are based on their contents and the use of language.

The software determines whether there are causal connections between the requirements, such as the data and meaning in one of the requirements depending on the other,or if the requirements are can be viewed as a special case of two-way causal dependencies.

The module combines various types of similarity metrics and formal analysis algorithms, to determine the relations between requirements. The formal analysis could also be relativized with respect to a given domain.

The categorization module solves two major tasks within requirement management: classification of requirements (top-bottom approach) and clustering of requirements (bottom-top approach).

The first task aims to automatically distribute all requirements into predetermined categories that are provided by the user of the system.

The second task, however, does not use preset categories, but rather groups the requirements into natural clusters based on the technical and linguistic data from the requirements, and thus determines the categories by itself without the involvement of the user.

Amongst the most important technologies, utilized by this module, are semantical analysis and artificial neural networks.

Contradictions are special types of relationship between requirements that involves high-level of analysis methodologies. Contradictions often arise when the requirements are gathered from multiple sources.

The REA contradictions module detects certain types of contradictions between pairs of imported requirements, and verifies the consistency of the whole set of requirements.

The module employs state-of-the-art techniques for automated verification that involve complex semantical and formal analysis, augmented with rule-based and ontology support. The formal analysis could also be relativized with respect to a given domain.

REA provides numerous visual services that display the results from the different analysis and extraction modules.

These visualizations include both, standard display formats such as diagrams, pie charts, and various graph representations, as well as customized formats that are unique to our specific type of analysis.

Visualization within the system is complemented with a number of export features that transform the data from REA into popular formats, which further helps the user to track and comprehend the automated analysis performed on the requirements.